Combustion of coal is one of the primary sources of electricity generation worldwide today. Coal contains different chemicals that cause particulate matter(PM) and sulfur dioxide (SO2) emissions. These are health hazards and are responsible for deteriorating the ambient air quality. Particulate matter also forms ash deposits inside the coal combustor, which in turn decreases the energy efficiency of the power plants. Using biomass as a fuel in these utility boilers can potentially reduce the problems of particulate matter emissions and ash deposition, and can significantly reduce the SO2 emissions. However, biomass needs to be pretreated to make its properties similar to coal in terms of energy density, grindability, and durability before it can be fired in utility boilers. Steam explosion is one of the leading biomass pretreatment methods that enhances the physicochemical properties of biomass. A comprehensive review of the steam explosion process, its product properties, its comparison with other treatment processes, as well as its economic analysis and lifecycle assessment, have been explored in this work. Steam-exploded biomass has been co-combusted with bituminous coal in a 1500 kWth combustor to analyze the ash aerosol particle size distribution, composition, and deposition behavior. The primary results of these tests showed that both particulate matter emissions and ash deposition amount reduced significantly as more biomass was co-fired with coal. The submicron-sized particulate matter concentration showed a high correlation with the final mass of ash deposits (R2 > 0.96). Predicting ash deposition rates is important during the combustion of solid fuels. A Machine Learning tool was applied and trained with a fuel composition database of 92 fuels obtained from a thermodynamic equilibrium software (FactSage). When fully operational, this model should be integrated with an existing ash deposition model, which should make it self-sufficient in terms of generating equilibrium composition data. SO2 emissions were analyzed during the co-combustion of biomass and coal, and a synergistic decrease in SO2 emissions was observed with higher biomass blends. Experiments were conducted in a full-scale 471 MWe furnace to analyze the SO2 emissions, and an 85%-15% blend of coal and biomass was responsible for a 28.1% reduction in emissions and 22.1% reduction in the lime slurry utilization in the flue gas desulfurization (FGD) towers compared to pure coal combustion. Ash deposit characterizations by energy dispersive X-ray spectroscopy (EDS) and X-ray diffraction (XRD) combined with thermodynamic equilibrium simulations revealed that calcium and potassium were responsible for this synergistic reduction as these metals captured the SO2 from the flue gases and retained them in the ash phase. The SO2 research was important since the current literature is deficient in research conducted at suspension-fired full-scale utility boilers to reduce SO2 emissions by co-firing coal and biomass blends. The research in this dissertation should provide valuable insights to the energy industries that are considering a transformation of fuel portfolio from coal to biomass and explore how the mineral matter present in pretreated biomass would behave inside a utility boiler. The primary conclusions are that during the co-combustion of coal and biomass, ash deposition mass and particulate matter ash load decreased, and SO2 emission saw a synergistic reduction in emissions due to higher calcium and potassium content in biomass compared to pure coal combustion.

Various potential methods and techniques for modifying surfaces to make themless sensitive to contamination have been researched for various applicationsbefore, to varying degrees of success. These are discussed in detail to potentiallyapply them in the automotive sector, to face the increasing technical cleanlinessrequirements, that are linked to more complexity in design and electrification. TheTheoretical background in dust adhesion and contact mechanics is discussed, withdevelopments in analytical and numerical methods highlighted. Then, someexamples of the surfaces in question are presented, and their topographiesmeasured. Potential techniques are identified from previous experimental research in otherfields, and their applicability and feasibility are discussed within the limits ofavailable data, then an attempt at a structured approach for choosing candidatesfor further experimental testing on a case by case basis is laid out, and suggestionsfor more comprehensive research into effective parameters and analytical methodsare made.

[pt] Uma preocupação significativa durante a produção de óleo e gás é a garantia de escoamento para evitar desperdício de tempo e dinheiro. Devido às mudanças nas condições durante a produção (como pressão e temperatura), principalmente na região do pré-sal brasileiro, a solubilidade dos componentes do petróleo bruto (óleo-gás-água) pode diminuir, resultando na formação de depósitos. A incrustação é geralmente causada por parafina, hidratos e sal inorgânico. Neste trabalho, foram desenvolvidos modelos utilizando estratégias de Aprendizado de Máquina para monitoramento da formação de incrustações inorgânicas e medição de parâmetros de processo associados com formas de remediação de obstruções de outras fontes. Primeiramente, foram criados modelos do processo de formação de incrustação de carbonato de cálcio na presença de monoetilenoglicol (inibidor de hidrato) usando a arquitetura de redes neurais feedfoward prever o pressão diferencial um e cinco instantes à frente, obtendo um R2 superior a 92,9 porcento para ambos os horizontes de predição. O segundo tópico explorado foi desenvolver modelos para determinação do pH em sistemas pressurizados (até 6,0 MPa) por meio de análise de imagens. Podendo ser aplicados no monitoramento de sistemas como Sistema Gerador de Nitrogênio, utilizado para remediar alguns problemas de incrustação, dado que sua cinética depende fortemente do pH do sistema. Foram criados modelos de classificação para o pH do sistema (2, 3, 4, 5, 6, 7, 8, 9, 10) usando Redes Neurais Convolucionais (CNN), Máquina de Vetor de Suporte e Árvores de Decisão. Além disso, modelos CNN foram construídos para predizer o pH na faixa de 2- 10. / [en] A significant concern during oil and gas production is flow assurance to avoid loss of time and money. Due to production conditions changes (such as pressure and temperature), especially in the Brazilian pre-salt region, the solubility of the components of the crude oil (oil-gas-water) can decrease, resulting in the formation of deposits. The fouling is usually caused by wax, gas hydrate, and inorganic salt (scale). In this work, models were developed using Machine Learning strategies for scale formation monitoring and measuring process parameters associated with remediation of obstruction from other sources. First, models for the calcium carbonate scaling formation process in the presence of monoethylene glycol (typical gas hydrate inhibitor) were created using feedforward neural network architecture to predict the differential pressure (deltaP) one and five steps ahead, obtaining an R2 higher than 92.9 percent for the training and test group for both the prediction horizon. The second approach explored was the development of models for determining the pH in atmospheric and pressurized systems (up to 6.0 MPa) using image analysis. These models could be applied to control and monitor the Nitrogen Generation System, which can be used for different flow assurance problems, and its kinetics strongly depend on the system s pH value. This step initially created classification models for the system pH (2, 3, 4, 5, 6, 7, 8, 9, 10) using the Convolution Neural Networks (CNN), Support Vector Machine, and decision tree architectures. Also, CNN models were built to predict the pH in the range of 2-10.

Shell and tube heat exchangers (STHEs) are the most common type of heat exchanger in preheat trains (PHT) of oil refineries and in chemical process plants. Most commercial design software tools for STHE assume uniform distribution over all tubes of a tube bundle. This leads to various challenges in the operation of the affected devices. Flow maldistribution reduces heat duty of STHE in many applications and supports fouling buildup in fluids that tend to particle, bio, and crystallization fouling (Verein Deutscher Ingenieure, ed., 2010, Heat Atlas, 2nd ed., VDI-Buch., Springer-Verlag). In this article, a fluid mechanics study about tube side flow distribution of crude oil and related hydrocarbons in two-pass PHT heat exchangers is described. It is shown that the amount of flow maldistribution varies significantly between the different STHE designs. Therefore, a parameter study was conducted to investigate reasons for maldistribution. For instance, the nozzles diameter, type, and orientation were identified as crucial parameters. In consequence, simple design suggestions for reducing tube side flow maldistribution are proposed.

Macromolecular biomaterials often require covalent crosslinking to achieve adequate stability and mechanical strength for their given application. However, the use of auxiliary chemicals may be associated with long-term toxicity in the body. Oppositely-charged polyelectrolytes (PEs) have the advantage that they can self-crosslink electrostatically and those derived from marine organisms are an inexpensive alternative to glycosaminoglycans present in the extracellular matrix of human tissues. A range of different combinations of PEs and preparation conditions have been reported in the literature. However, although there has been some work on complex formation between chitosan (CS) and carrageenan (CRG), much of the work undertaken has ignored the effect of pH on the consequent physicochemical properties of self-crosslinked polyelectrolyte complex (PEC) gels, films and scaffolds. Chitosan is a positively-charged polysaccharide with NH3+ side groups derived from shrimp shells and, carrageenan is a negatively-charged polysaccharide with OSO3- side groups derived from red seaweed. These abundant polysaccharides possess advantageous properties such as biodegradability and low toxicity. However, at present, there is no clear consensus on the cell binding properties of CS and CRG or CS-CRG PEC materials. The aim of this study was to explore the properties of crosslinker-free PEC gels, solvent-cast PEC films and freeze-dried PEC scaffolds based on CS and CRG precursors for medical applications. The objective was to characterise the effect of pH of the production conditions on the physicochemical and biological properties of CS-CRG PECs. Experimental work focused on the interaction between PEs, the composition of PECs, the rheological properties of PEC gels and the mechanical properties of PEC films and scaffolds. In addition, cell and protein attachment to the PEC films was assessed to determine their interactions in a biological environment. For biomedical applications, these materials should ideally be stable when produced such that they can be processed to form either a film or a scaffold and have mechanical properties comparable to those of collagenous soft tissues. FTIR was used to confirm PEC formation. Zeta potential measurements indicated that the PECs produced at pH 2-6 had a high strength of electrostatic interaction with the highest occurring at pH 4-5. This resulted in stronger intra-crosslinking in the PEC gels which led to the formation of higher yield, solid content, viscosity and fibre content in PEC gels. The weaker interaction at pH 7-12 resulted in higher levels of CS incorporated into the complex and the formation of inter-crosslinking through entanglements between PEC units. This resulted in the production of strong and stiff PEC films and scaffolds appropriate for soft tissue implants. The PECs prepared at pH 7.4 and 9 also exhibited low swelling and mass loss, which was thought to be due to the high CS content and entanglements. From the range of samples tested, the PECs produced at pH 7.4 appeared to show the optimum combination of yield, stability and homogeneity for soft tissue implants. Biological studies were performed on CS, CRG and PECs prepared at pH 3, 5, 7.4 and 9. All of the PE and PEC films were found to be non-cytotoxic. When the response of three different cell types and a high binding affinity protein (tropoelastin) was evaluated; it was found that the CS-CRG PEC films displayed anti-adhesive properties. Based on these experimental observations and previous studies, a mechanistic model of the anti-adhesive behaviour of PEC surfaces was proposed. It was therefore concluded that the CS-CRG PECs produced might be suitable for non-biofouling applications.

Modeling of heat transfer using Dymola. In this report a evaporator, economizer and superheater where modeled. The report describes how the models where modeled and what input was most suitable for a accurate model.

published_or_final_version / abstract / Environmental Management / Master / Master of Science in Environmental Management

A conventional membrane bioreactor (MBR) and two moving bed bioreactors coupled with ultrafiltration membrane filtration were operated for close to six months to investigate biological nutrient removal and potential fouling inducing parameter mitigation. Unique to one of the moving bed membrane bioreactors (MBMBR) was a newly designed media that incorporated a hydrodynamic exterior carrier with a highly porous interior packing. Preliminary investigation indicates that nitrogen compounds were superiorly removed in the two MBMBRs when compared with the MBR. This is a result of denitrification processes occurring in anoxic micro-zones found within the depths of the biofilm affixed to media. Fouling propensity was found to be increased by over four times in the MBMBR systems as compared to the MBR. Mixed liquor, permeate and filtrate analysis, membrane fibre examination and permeability tests indicated that colloidal organic carbon, as well as soluble microbial products were the dominant fouling inducing compounds. / Manuscript format / The Natural Sciences and Engineering Research Council of Canada

名古屋大学年代測定総合研究センターシンポジウム報告

The rapid increase in the demand on fresh water due the increase in the world population and scarcity of natural water puts more stress on the desalination industrial sector to install more desalination plants around the world. Among these desalination plants, multistage flash desalination process (MSF) is considered to be the most reliable technique of producing potable water from saline water. In recent years, however, the MSF process is confronting many problems to cut off the cost and increase its performance. Among these problems are the non-condensable gases (NCGs) and the accumulation of fouling which they work as heat insulation materials. As a result, the MSF pumps and the heat transfer equipment are overdesigned and consequently increase the capital cost and decrease the performance of the plants. Moreover, improved process control is a cost effective approach to energy conservation and increased process profitability. Thus, this study is motivated by the real absence of detailed kinetic fouling model and implementation of advance process control (APC). To accomplish the above tasks, commercial modelling tools can be utilized to model and simulate MSF process taking into account the NCGs and fouling effect, and optimum control strategy. In this research, gPROMS (general PROcess Modeling System) model builder has been used to develop the MSF process model. First, a dynamic mathematical model of MSF is developed based on the basic laws of mass balance, energy balance and heat transfer. Physical and thermodynamic properties of brine, distillate and water vapour are included to support the model. The model simulation results are validated against actual plant data published in the literature and good agreement with these data is obtained. Second, the design of venting system in MSF plant and the effect of NCGs on the overall heat transfer coefficient (OHTC) are studied. The release rate of NCGs is studied using Henry’s law and the locations of venting points are optimised. The results reveal that high concentration of NCGs heavily affects the OHTC. Furthermore, advance control strategy namely: generic model control (GMC) is designed and introduced to the MSF process to control and track the set points of the two most important variables in the MSF plant; namely the Top Brine Temperature (TBT) which is the output temperature of the brine heater and the Brine Level (BL) in the last stage. The results are compared to conventional Proportional Integral Derivative Controller (PID) and show that GMC controller provides better performance over conventional PID controller to handle a nonlinear system. In addition, a new control strategy called hybrid Fuzzy-GMC is developed and implemented to control the same aforementioned loops. Its results reveal that the new control outperforms the pure GMC in some areas. Finally, a dynamic fouling model is developed and incorporated into the MSF dynamic process model to predict fouling at high temperature and high velocity. The proposed dynamic model considers the attachment and removal mechanisms of calcium carbonate and magnesium hydroxide with more relaxation of the assumptions. Since the MSF plant stages work as a series of heat exchangers, there is a continuous change of temperature, heat flux and salinity of the seawater. The proposed model predicts the behaviour of fouling based on the physical and thermal conditions of every single stage of the plant.